Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
8-2022
Abstract
Restless Multi-Armed Bandits (RMAB) is an apt model to represent decision-making problems in public health interventions (e.g., tuberculosis, maternal, and child care), anti-poaching planning, sensor monitoring, personalized recommendations and many more. Existing research in RMAB has contributed mechanisms and theoretical results to a wide variety of settings, where the focus is on maximizing expected value. In this paper, we are interested in ensuring that RMAB decision making is also fair to different arms while maximizing expected value. In the context of public health settings, this would ensure that different people and/or communities are fairly represented while making public health intervention decisions. To achieve this goal, we formally define the fairness constraints in RMAB and provide planning and learning methods to solve RMAB in a fair manner. We demonstrate key theoretical properties of fair RMAB and experimentally demonstrate that our proposed methods handle fairness constraints without sacrificing significantly on solution quality.
Keywords
Child care, Decision-making problem, Decisions makings, Efficient resource allocation, Expected values, Fairness constraints, Health interventions, Personalized recommendation, Restless multi-armed bandit, Sensor monitoring
Discipline
Databases and Information Systems | Information Security
Research Areas
Data Science and Engineering; Intelligent Systems and Optimization
Areas of Excellence
Digital transformation
Publication
Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence, (UAI 2022), Eindhoven, Netherlands, 2022 August 1-5
Volume
38
First Page
1158
Last Page
1167
ISBN
9781713863298
Publisher
AUAI Press
City or Country
USA
Citation
LI, Dexun and VARAKANTHAM, Pradeep.
Efficient resource allocation with fairness constraints in restless multi-armed bandits. (2022). Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence, (UAI 2022), Eindhoven, Netherlands, 2022 August 1-5. 38, 1158-1167.
Available at: https://ink.library.smu.edu.sg/sis_research/9095
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.